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The purpose of this study is to analyze and develop alternative forecasting techniques for both demand averages and demand variation for Economic Order Quantity (EOQ) items. Currently demand average forecasts are used to determine the operating level and order and ship time (O & ST) quantity. An estimate of demand variation is currently used to compute the safety level quantity. We compare the current and alternative forecasting techniques using demand histories simulated over 50 years. We found the current method provides as accurate an estimate of average demand as any other method we tested. However the current system's estimate for demand variation is inadequate. Statistical analysis of actual Air Force EOQ item's demand history supports the conclusion that estimates of demand variation are inadequate. The current system underestimates the demand variance for over 40% of the Air Force EOQ items. We compare six alternative methods for estimating and using demand variation. We use the System to Analyze and Simulate Base Supply (SASBS) model to evaluate the effectiveness and efficiency of the six alternative techniques. The method that computes the actual variance of demand and order and ship time and places a ceiling on the safety level is the method we recommend. We recommend the safety level computation at base level be modified to accurately measure demand variation and include order and ship time variation. We also present another method which also accurately measures demand and order and ship time variation. This method provides most of the benefits but at reduced costs.Read more...

Abstract:

The purpose of this study is to analyze and develop alternative forecasting techniques for both demand averages and demand variation for Economic Order Quantity (EOQ) items. Currently demand average forecasts are used to determine the operating level and order and ship time (O & ST) quantity. An estimate of demand variation is currently used to compute the safety level quantity. We compare the current and alternative forecasting techniques using demand histories simulated over 50 years. We found the current method provides as accurate an estimate of average demand as any other method we tested. However the current system's estimate for demand variation is inadequate. Statistical analysis of actual Air Force EOQ item's demand history supports the conclusion that estimates of demand variation are inadequate. The current system underestimates the demand variance for over 40% of the Air Force EOQ items. We compare six alternative methods for estimating and using demand variation. We use the System to Analyze and Simulate Base Supply (SASBS) model to evaluate the effectiveness and efficiency of the six alternative techniques. The method that computes the actual variance of demand and order and ship time and places a ceiling on the safety level is the method we recommend. We recommend the safety level computation at base level be modified to accurately measure demand variation and include order and ship time variation. We also present another method which also accurately measures demand and order and ship time variation. This method provides most of the benefits but at reduced costs.